Grey Level Estimation for Discrete Tomography
Discrete tomography is a powerful approach for reconstructing images that contain only a few grey levels from their projections. Most theory and reconstruction algorithms for discrete tomography assume that the values of these grey levels are known in advance. In many practical applications, however, the grey levels are unknown and difficult to estimate. In this paper, we propose a semi-automatic approach for grey level estimation that can be used as a preprocessing step before applying discrete tomography algorithms. We present experimental results on its accuracy in simulation experiments.
KeywordsGrey Level Penalty Function Reconstruction Algorithm Projection Data Projection Angle
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